Author Archives: X1

June 30, 2021 · 2:21 PM

Relativity and X1 Publish Joint Legal Whitepaper on ESI Collection Best Practices

By John Patzakis

Relativity and X1 have published a joint legal whitepaper on the topic of full-disk imaging as a disfavored collection practice in civil litigation, with Relativity eDiscovery attorney David Horrigan as the lead author. The paper delves into all the legal reasons, including detailed analysis of case law, the Federal Rules of Civil Procedure, and the Sedona Principles establishing why forensic collection is not required in civil litigation. The paper primarily focuses on the principles of proportionality in its legal analysis as well as case law issued prior to the 2015 amendment to the Federal Rules of Civil Procedure, which gave greater prominence and clarification of the proportionality rules.


This is an important topic as a key problem in eDiscovery that drives inefficiencies and higher costs is that default collection methods often involve full-disk imaging—a forensic examination of an entire computer—when searching for responsive data. As the whitepaper notes, “it turns out full-disk imaging is not required for most eDiscovery collections. In fact, courts often disfavor the practice.”


A copy of the whitepaper can be found here.

Leave a comment

Filed under Authentication, Best Practices, Case Law, eDiscovery, ESI, law firm, Preservation & Collection, proportionality

May 12, 2021 · 10:12 AM

X1 Social Discovery Case Law Update

by John Patzakis

X1 Social Discovery had a key mention in a US Federal Court decision published last week. Edwards v. Junior State of America Foundation, No. 4:19-CV-140-SDJ, (US Dist. CT, E.D. Texas April 23, 2021), is a civil litigation matter involving the intentional destruction (spoliation) of social media evidence. The plaintiff had deleted his Facebook account resulting in lost evidence critical to the case. The court cited an affidavit submitted by an eDiscovery expert witness who noted that when X1 Social Discovery was used to collect from the Plaintiff’s Facebook account, key evidence that existed prior to the litigation was missing because it had been deleted by the Plaintiff prior to the X1 Social Discovery collection.

As a result of the spoliation established in large part by the X1 Social Discovery examination, the Court imposed severe evidentiary sanctions on the plaintiff, including the exclusion of evidence and claims related to the destroyed Facebook data, and adverse jury instructions. This case once again illustrates the critical importance of social media evidence and the need to both properly preserve key social media evidence in not only a comprehensive manner, but also as soon as possible when actual or constructive notice of the litigation arises.

As we have documented extensively on this blog, the outcome of numerous cases have been determined by the improper destruction of social media evidence. Jury awards in civil cases have been overturned, criminal convictions have been thrown out and attorneys disbarred because social media evidence was not properly preserved utilizing best practices.

In fact, in another case decided last week, an Oregon trial court in a criminal matter had excluded key Facebook evidence because the prosecution failed to properly authenticate the Facebook evidence. In State of Oregon v. Acosta, 311 Or.App. 136 (May 5, 2021), the prosecution offered no forensics or technical evidence to establish an evidentiary foundation for the offered social media evidence, and instead relied upon screenshots and witness testimony. After the trial court excluded the prosecution’s social media evidence on the grounds of insufficient authentication, the case was brought up on appeal and the appellate court ended up reversing in a very close call, finding that the offered non-forensic witness testimony offered was sufficient. However, in many other cases the proponent of the social media evidence using mere screenshots have not been as successful, and this whole appeal could have been avoided by the government if they had used best practices. In fact, when X1 Social Discovery is used to collect and authenticate social media and other web-based data, the evidence is not only properly authenticated, but costly protracted court proceedings and appeals such as in the two cases above is avoided. When X1 Social Discovery is used, our customers report that it encourages evidentiary stipulations for the admission of the collected data under Federal Rule of Evidence 902(14) or similar state rules.

Leave a comment

Filed under Best Practices, Case Law, eDiscovery, law firm, Preservation & Collection, Social Media Investigations, Social Media Metadata

May 4, 2021 · 11:18 AM

Industry Experts from Relativity and Insight Optix Discuss Operationalizing Proportionality

By John Patzakis

Industry experts including Relativity eDiscovery attorney David Horrigan, Relativity Product Manager Greg Evans and Insight Optix CEO Mandi Ross addressed utilizing cutting-edge ESI collection processes and technologies to effectuate proportionality in a recent webinar. Under Federal Rule of Civil Procedure 26(b)(1), parties may discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. Lawyers that take full advantage of the proportionality rule can greatly reduce cost, time and risk associated with otherwise inefficient eDiscovery. While proportionality is an often-discussed ideal sought by most legal stakeholders, especially corporate counsel, the discussion focused on how to use processes and best practices to operationally attain this goal.

David Horrigan first provided a detailed analysis of Rule 26(b)(1), and some key case law applying the proportionality rule, including McMaster v. Kohl’s Dep’t Stores, Inc., No. 18-13875 (E.D. Mich. July 24, 2020). Horrigan commented that McMaster generally supports the application of a process that effectively applies proportionality on an operational basis through an iterative exercise to identify relevant custodians, their data sources, applicable data ranges, file types and agreed upon keywords. Such a “targeted, automated and proportional” collection process can be applied to collect only the data that is responsive to this specific criteria.

Mandi Ross explained that proportionality is getting a further boost as George Washington University Law School is sponsoring the development of an important proportionality benefit-and-burden model that provides a practical structure for assessing claims of proportionality. The model features a heat map mechanism to identify relevant custodians and data sources to enable a more objective application of proportionality, thereby facilitating negotiations and better informing the bench. Mandi is key leader of a team of industry legal and technology exports drafting the GW Law model.

Mandi then outlined her typical workflow applying the aforementioned proportionality heat map in an iterative manner to identify key custodians, data sources, and the potentially relevant data itself. To effectuate this, Mandi noted that “X1 Distributed Discovery and Relativity Collect gives us the ability to understand the story the data tells, using (X1’s) index in-place and also allows us to optimize and target our collection efforts.”

To illustrate Mandi’s point, the webinar then featured a live demonstration showing X1 quickly collecting data across custodians from their laptops, fileservers or other network sources, and seamlessly importing that data into RelativityOne in minutes. Relativity Product Manager Greg Evans outlined how the Relativity/X1 integration streamlines eDiscovery processes by collapsing the many hand-offs built into current EDRM workflows to provide greater speed and defensibility. Evans also said that new normal of web-enabled collections of remote custodians and data sources was a major driver for the Relativity/X1 alliance, as “remote collections now represent 90 percent of all eDiscovery collections happening right now.”

The live demonstration performed by Greg Evans highlighted in real time how the integration improves the enterprise eDiscovery collection and ECA process by enabling a targeted, automated and proportional search and collection process, with immediate pre-collection visibility into custodial data. X1 Distributed Discovery enhances the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome electronically stored information (ESI) processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection.

A recording of the webinar on proportionality can be accessed here.

And a link directly to the demo featuring the X1 and Relativity integration can be accessed here.

Leave a comment

Filed under Uncategorized

April 6, 2021 · 10:23 AM

On TAP: Targeted, Automated, and Proportional Collection for Modern e-Discovery

By John Patzakis

Proportionality is now the hottest legal issue in the area of eDiscovery, with the largest number of eDiscovery-related cases in the past year addressing the subject. eDiscovery attorney Kelly Twigger leads a team who produced an excellent analysis of 2020 case law, noting “a big jump to 889 in 2020” of cases addressing proportionality, “which represented nearly a third (31%) of all (eDiscovery) case law decisions last year.” The report notes that “[p]roportionality arguments have become a weapon in arguing scope of discovery and the sharp rise in disputes has illustrated the need for more systematic and standardized approaches to assessing proportionality in cases today.” 

Proportionality-based eDiscovery is a goal that all judges and corporate attorneys want to attain. Under Federal Rule of Civil Procedure 26(b)(1), parties may discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. Lawyers that take full advantage of the proportionality rule can greatly reduce cost, time and risk associated with otherwise inefficient eDiscovery.

Proportionality is getting a further boost as George Washington University Law School is developing an important proportionality benefit-and-burden model that provides a practical structure for assessing claims of proportionality. The model features a heat map mechanism to identify relevant custodians and data sources to enable a more objective application of proportionality, thereby facilitating negotiations and better informing the bench.

The GW Law model is much needed, as while there is keen awareness of proportionality in the legal community, attaining the benefits requires the ability to operationalize workflows as far upstream in the eDiscovery process as possible. For instance, when you’re engaging in data over-collection, which in turn runs up of a lot of human time and processing costs, the ship has largely sailed before you are able to perform early case assessments and data relevancy analysis, as much of the discovery costs have already been incurred at that point. The case law and the Federal Rules provide that the duty to preserve only applies to potentially relevant information, but unless you have the right operational processes in place, you’re losing out on the ability to attain the benefits of proportionality.

An example of a process that effectively applies proportionality on an operational basis would be an iterative exercise to identify relevant custodians, their data sources, applicable data ranges, file types and agreed upon keywords, following the process outlined in  McMaster v. Kohl’s Dep’t Stores, Inc., No. 18-13875 (E.D. Mich. July 24, 2020), and collect only the data that is responsive to this specific criteria. The latest enterprise collection tech from Relativity and X1 enable such detailed and proportional criteria to be applied in-place, at the point of collection. This reduces the data volume funnel by as much as 98 percent from over-collection models, yet with increased transparency and compliance. In other words, a collection process that targeted, automated and proportional, instead of one that is overbroad and manual.

To learn more about these concepts, please tune in on April 13, where attorney David Horrigan of Relativity and Mandi Ross of Prism Litigation Technology will be leading a webinar to discuss the legal and operational considerations and benefits of proportionality. The webinar will also feature a live exercise performing a pre-collection proportionality analysis on remote employee data. You can register here.

Leave a comment

Filed under Best Practices, Case Law, ECA, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, ESI, law firm, Preservation & Collection, proportionality

March 15, 2021 · 4:33 PM

Why Post-Level Parsing is Critical for Effective Social Media Evidence Collection

By John Patzakis

As succinctly noted by The Florida Bar Association in its publication, Florida Law Journal: “Social media is everywhere. Nearly everyone uses it. Litigants who understand social media–and its benefits and limitations–can immeasurably help their clients resolve disputes…it is inevitable that the social media accounts of at least one person involved in a dispute will have potentially relevant and discoverable information.“ “Social Media Evidence: What You Can’t Use Won’t Help You” Florida Law Journal, Volume 88, No. 1.

The high volume of relevant social media evidence means that lawyers are under an ethical duty of competence to address and account for it in their litigation and compliance matters. For this reason, there has been a strong demand for social media evidence collection software and services. However, Facebook, the most widely used social media platform, rolled out a completely new interface and data format in the latter part of 2020 for all their 2.4 billion users. This broke every social media evidence tool on the market, causing a major disruption of eDiscovery and compliance workflows. In response, social media evidence collection tools either exited the market, changed their model to services, or provided flat file screen shots as their output.

Flat file screen shots of social media are of limited value, as what they generally entail is a screenshot image file without metadata, other than what is visible on the image itself. This is problematic as there are many important but hidden metadata fields associated with social media posts that need to be parsed and populated into the appropriate fields associated with the post. Also, flat images do not enable effective text extraction, and it is impossible to cull, process, display, and apply analytics to flat file outputs in attorney review platforms such as Relativity. Associated comments to a post are not collected, or at best are truncated and not displayed in line.

Conversely, post-level native collection of social media is ideal, because it enables the collection of the social media post as a parent item with all associated metadata and comments preserved and displayed inline. This will enable the automated generation of robust load files that include date stamps and other key metadata, extracted text for searching, family post identification and associated comments. Additionally, post-level hash values can be readily generated at the point of collection and verified to establish evidentiary authentication.  All this enables a very fluid and scalable workflow that dramatically reduces downstream processing and review platform upload costs.

With the recent release of version 5.12, X1 Social Discovery is the only eDiscovery solution to provide post-level parsing for Facebook timeline posts in the new Facebook format, as well as for Twitter feeds. To learn more about this important functionality, watch the webinar.

Leave a comment

Filed under Uncategorized